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   "source": [
    "# Scraping And Parsing A Wikipedia List into Pandas\n",
    "\n",
    "- **Author:** [Chris Albon](http://www.chrisalbon.com/), [@ChrisAlbon](https://twitter.com/chrisalbon)\n",
    "- **Date:** -\n",
    "- **Repo:** [Python 3 code snippets for data science](https://github.com/chrisalbon/code_py)\n",
    "- **Note:** -"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preliminaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Import required modules\n",
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a beautiful soup object from the website"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Create a variable with the URL to this tutorial\n",
    "url = 'http://en.wikipedia.org/wiki/List_of_airship_accidents'\n",
    "\n",
    "# Scrape the HTML at the url\n",
    "r = requests.get(url)\n",
    "\n",
    "# Turn the HTML into a Beautiful Soup object\n",
    "soup = BeautifulSoup(r.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parse the html into a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Create a list for the scraping results\n",
    "disasters = []"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The structure of the page is such that if we take all the *li* items **without** a tag, and then ignore the last three, we will have a clean list of all the disasters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Create a list elment for each li without a class (except for the last three)\n",
    "# Then, for each row, append the text to disasters. \n",
    "for row in soup.find_all('li', class_=False)[:-3]: \n",
    "    disasters.append(row.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data wrangle the list into a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Create a dataframe from the list\n",
    "df = pd.DataFrame(disasters, columns=['raw'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Take everything before the \":\" and call that the date variable\n",
    "df['date'] = df['raw'].str.extract('(^[^_]+(?=:))')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Take everything after the \":\" and call that the description variable\n",
    "df['description'] = df['raw'].str.extract('\\:(.*)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Set the date variable to be time\n",
    "df['date'] = pd.to_datetime(df['date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Set the date variable to be the dataFrame's index\n",
    "df.index = df['date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Drop the variables we no longer need\n",
    "df = df.drop(['raw', 'date'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2 May 1902</th>\n",
       "      <td>  Semi-rigid airship Pax explodes over Paris, k...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13 October 1902</th>\n",
       "      <td>  Separation of gondola from envelope over Pari...</td>\n",
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       "      <th>30 November 1907</th>\n",
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       "      <th>23 May 1908</th>\n",
       "      <td>  Morrell airship falls over Berkeley, Californ...</td>\n",
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       "    <tr>\n",
       "      <th>4 August 1908</th>\n",
       "      <td>  Zeppelin LZ 4 caught fire near Echterdingen a...</td>\n",
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       "                                                        description\n",
       "date                                                               \n",
       "2 May 1902         Semi-rigid airship Pax explodes over Paris, k...\n",
       "13 October 1902    Separation of gondola from envelope over Pari...\n",
       "30 November 1907   Loss of the French Army's Patrie - no fatalit...\n",
       "23 May 1908        Morrell airship falls over Berkeley, Californ...\n",
       "4 August 1908      Zeppelin LZ 4 caught fire near Echterdingen a..."
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   "source": [
    "# View the top of the dataframe\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": false
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   "outputs": [],
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